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Advances in Meteorology
Volume 2015 (2015), Article ID 545376, 12 pages
Research Article

Calibration of Conceptual Rainfall-Runoff Models Using Global Optimization

1Key Laboratory of Ministry of Education for Geomechanics and Embankment Engineering, Hohai University, Nanjing 210098, China
2Research Institute of Geotechnical Engineering, Hohai University, Nanjing 210098, China
3Department of Civil & Environmental Engineering, University of Waterloo, Waterloo, ON, Canada N2L 3G1

Received 19 November 2014; Revised 9 February 2015; Accepted 19 February 2015

Academic Editor: Hann-Ming H. Juang

Copyright © 2015 Chao Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Parameter optimization for the conceptual rainfall-runoff (CRR) model has always been the difficult problem in hydrology since watershed hydrological model is high-dimensional and nonlinear with multimodal and nonconvex response surface and its parameters are obviously related and complementary. In the research presented here, the shuffled complex evolution (SCE-UA) global optimization method was used to calibrate the Xinanjiang (XAJ) model. We defined the ideal data and applied the method to observed data. Our results show that, in the case of ideal data, the data length did not affect the parameter optimization for the hydrological model. If the objective function was selected appropriately, the proposed method found the true parameter values. In the case of observed data, we applied the technique to different lengths of data (1, 2, and 3 years) and compared the results with ideal data. We found that errors in the data and model structure lead to significant uncertainties in the parameter optimization.